Abstract

Pointcut fragility is a well-documented problem in Aspect-Oriented Programming; changes to the base-code can lead to join points incorrectly falling in or out of the scope of pointcuts. We present an automated approach that limits fragility problems by providing mechanical assistance in pointcut maintenance. The approach is based on harnessing arbitrarily deep structural commonalities between program elements corresponding to join points selected by a pointcut. The extracted patterns are then applied to later versions to offer suggestions of new join points that may require inclusion. We demonstrate the usefulness of our technique by rejuvenating pointcuts in multiple versions of several open-source AspectJ programs. The results show that our parameterized heuristic algorithm was able to automatically infer new join points in subsequent versions with an average recall of 0.93. Moreover, these join points appeared, on average, in the top 4th percentile of the suggestions, indicating that the results were precise.